Codes
Tick Chart for MetaTrader 4
The presented indicator plots a fully-functional tick chart similar to the standard price charts, with the ability of the analysis using all the MetaTrader features
Articles
Neural Networks in Trading: Generalizing Time Series Without Data-Specific Dependence (Mamba4Cast) for MetaTrader 5
In this article, we introduce the Mamba4Cast framework and take a closer look at one of its key components: timestamp-based positional encoding. The article shows shows how time embedding is formed taking into account the calendar structure of the data
Neural Networks in Trading: Time Series Forecasting Using Adaptive Modal Decomposition (Final Part) for MetaTrader 5
The article discusses the adaptation and practical implementation of the ACEFormer framework using MQL5 in the context of algorithmic trading. It presents key architectural decisions, training features, and model testing results on real data
Neural Networks in Trading: Time Series Forecasting Using Adaptive Modal Decomposition (ACEFormer) for MetaTrader 5
We invite you to explore the ACEFormer architecture — a modern solution that combines the effectiveness of probabilistic attention with adaptive time series decomposition. This article will be useful for those seeking a balance between computational performance and forecast accuracy in financial
Neural Networks in Trading: LSTM Optimization for Multivariate Time Series Forecasting (Final Part) for MetaTrader 5
We continue to implement the DA-CG-LSTM framework, which offers innovative methods for time series analysis and forecasting. The use of CG-LSTM and dual attention allows for more accurate detection of both long-term and short-term dependencies in data, which is particularly useful for working with
Neural Networks in Trading: LSTM Optimization for Multivariate Time Series Forecasting (DA-CG-LSTM) for MetaTrader 5
This article introduces the DA-CG-LSTM algorithm, which offers new approaches to time series analysis and forecasting. It explains how innovative attention mechanisms and model flexibility can improve forecast accuracy
Neural Networks in Trading: Actor—Director—Critic (Final Part) for MetaTrader 5
The Actor–Director–Critic framework is an evolution of the classic agent learning architecture. The article presents practical experience of its implementation and adaptation to financial market conditions
Neural Networks in Trading: Actor—Director—Critic for MetaTrader 5
We invite you to explore the Actor-Director-Critic framework, which combines hierarchical learning and a multi-component architecture for creating adaptive trading strategies. In this article, we take a detailed look at how using the Director to classify the Actor's actions helps to effectively
Neural Networks in Trading: Skill Hierarchy for Adaptive Agent Behavior (Final Part) for MetaTrader 5
The article discusses the practical implementation of the HiSSD framework in algorithmic trading tasks. It explains how the skill hierarchy and adaptive architecture can be used to build sustainable trading strategies
Neural Networks in Trading: Hierarchical Skill Discovery for Adaptive Agent Behavior (HiSSD) for MetaTrader 5
In this article, we explore the HiSSD framework, which combines hierarchical learning and multi-agent approaches to create adaptive systems. We examine in detail how this innovative methodology helps uncover hidden patterns in financial markets and optimize trading strategies in decentralized
Neural Networks in Trading: Anomaly Detection in the Frequency Domain (Final Part) for MetaTrader 5
We continue to work on implementing the CATCH framework, which combines the Fourier transform and frequency patching mechanisms, ensuring accurate detection of market anomalies. In this article, we complete the implementation of our own vision of the proposed approaches and test the new models on